Your signal loss, measured
Tracked conversions compared with your order system.
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Privacy & cookieless
Cookieless tracking and privacy consulting.
Signal loss is not a future event, it is a current cost. This engagement assesses how much measurement you have already lost, what your consent and tracking setup is actually doing, and how to rebuild measurement on first-party foundations.
- Consent architecture
- Signal loss audit
- First-party strategy
What you get
Measure more, with less exposure.
Consent that actually works
Tags and server events audited under every consent state.
One system, not three projects
Consent, tracking and measurement designed together.
Measurement that lasts
A plan that stays viable as signal degrades further.
The problem
Compliant, and measuring far less than you think.
Two failures usually coexist. The consent banner was implemented to satisfy legal review, and it now blocks tracking in ways nobody has quantified, so reported conversions are down and the cause is attributed to performance. At the same time, tags fire before consent, or hashed identifiers get sent for users who opted out, creating genuine exposure. Both problems come from the same root: consent, tracking and measurement were treated as three separate projects owned by three different teams.
What the engagement covers
What's included.
- Signal loss quantification: what share of conversions and journeys you are actually observing today
- Consent implementation review against how tags and server-side events genuinely behave
- Consent Mode and platform-specific privacy feature configuration review
- A server-side tracking architecture recommendation, with identifier and consent handling designed in
- First-party data strategy: what to collect, where to store it, and how to use it for measurement
- A measurement plan that stays viable as signal degrades further, including where modeling replaces observation
How we work
How we run it.
Step 1
Measure the current gap between observed and actual conversions before recommending anything
Step 2
Audit what tags and events do under each consent state, in the browser and server-side
Step 3
Design the consent and tracking architecture as one system rather than separate fixes
Step 4
Deliver a phased plan covering both the compliance risks and the measurement rebuild
What we use
Tools, platforms and methods.
- Server-side GTM
- Consent Mode
- Conversions APIs
- CMP review
- BigQuery
- Snowflake
Related work
Projects we've delivered.
FAQ
Common questions.
Is this legal advice?
No, and it should not be treated as such. We assess technical implementation against how your policies and consent framework are configured, and we flag where behavior and stated policy diverge. Your counsel decides what your obligations are; we tell you what your systems are actually doing.
How much measurement do teams typically lose?
It varies widely by geography, device mix and consent design, so treat any single figure quoted at you with suspicion. What matters is your number, which is measurable by comparing tracked conversions to your order system. Establishing that baseline is the first thing we do, and it is often the most useful output.
Does server-side tracking bypass consent?
No, and any vendor implying otherwise is selling you risk. Server-side tracking improves durability against browser restrictions and ad blockers for users who have consented. Consent is still checked before an event is sent. Its value is reliability and control over the payload, not evasion.
What replaces user-level tracking for the parts we lose?
Aggregate and experimental methods, mainly: marketing mix modeling for channel-level allocation, geo holdouts for incrementality, and clean rooms for privacy-safe joins. The shift is from observing every path to measuring effects reliably, which for budget decisions is usually sufficient.
Go deeper
Guides from our engineers.
Guide
Server-Side CAPI at Agency Scale: The Implementation Guide
How to implement Meta Conversions API, Google Enhanced Conversions, and TikTok Events API server-side: deduplication, match quality, CRM enrichment, and multi-client rollout.
Read the guideGuide
First-Party Data Clean Rooms, Explained (AMC, Ads Data Hub & Beyond)
What data clean rooms are, how Amazon Marketing Cloud, Google Ads Data Hub, and Meta Advanced Analytics work, and when a clean room is worth the engineering investment.
Read the guideRelated
Related services.
Conversions API
Server-side tracking for Meta CAPI, Google Enhanced Conversions and TikTok Events API.
Learn moreMarketing mix modeling
Meridian or Robyn models fed by your own pipeline, to measure what each channel contributes.
Learn moreAmazon Marketing Cloud
AMC setup, audience uploads and queries, with clean room results in your own warehouse.
Learn moreQuantify your signal loss.
We will baseline how much measurement you are actually losing before recommending any rebuild.